Cross-domain meta-learning for bug finding in the source codes with a small dataset
Jong-Ho Shin · 2020
In terms of application security, detecting security vulnerabilities in prior and fixing them is one of the effective ways to prevent malicious activities. However, finding security bugs is highly reliant upon human experts due to its complexity. Therefore, source code auditing, one of the ways to find bugs, costs a lot, and the quality of auditing quite varies according to the performer. There have been many attempts to make automated systems for code auditing, but they have been suffered from huge false positives and false negatives.